SWOT, Empiricism, and River Modeling
Year: 2026
Type: article
Abstract: Given the insurmountable challenge of measuring all rivers in situ, global river models serve as the foundation of freshwater knowledge past, present, and future. We adopt an inductive empirical framework based on Surface Water and Ocean Topography (SWOT) satellite measurements to assess these models. After controlling for SWOT data quality, we examine 68,347 individual river reaches representing ∼38% of global discharge. We find river models currently struggle in areas of heavy economic development, multi‐channel rivers, arid areas, and many Arctic rivers. After controlling for these expected errors, we find better skill as rivers get wider and that parts of Siberia and China are particularly difficult to model. We also find large variability and spatial heterogeneity to model performance, resisting oversimplification. Our results suggest that leveraging SWOT observations within river models will improve them, but river models must adapt their structure to represent realistic hydraulics to do so.
Source: Geophysical Research Letters
DOI: 10.1029/2026gl124323
Authors: Colin J. Gleason, Paul D. Bates, Michael T. Durand, Dongmei Feng, Augusto Getirana, Peirong Lin, Hind Oubanas, Tamlin M. Pavelsky, Chaopeng Shen, Laurence C. Smith, Jida Wang, Dai Yamazaki, Yuan Yang, Heejin An, Fiona B. Bennitt, Stephen J. Chuter, Chenqi Fang, Jonathan A. Flores, Elisa Friedmann, Sreelekha Jarugula, Haoyu Ji, Theodore Langhorst, Di Long, Dung T. Vu, Ziyun Yin, George H. Allen, Konstantinos M. Andreadis, Sylvain Biancamaria, Casey M. Brown, Cédric H. David, Ming Pan, Jeffrey C. Neal, Stephen P. Coss, Merritt E. Harlan, Peyman Saemian, Travis T. Simmons, Nikki Tebaldi, M. J. Tourian
Institutions: University of Massachusetts Amherst, University of Bristol, Fathom (United Kingdom), Byrd Polar and Climate Research Center, The Ohio State University, University of Cincinnati, Goddard Space Flight Center, Science Systems and Applications (United States), Peking University, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, AgroParisTech, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Gestion de l'Eau, Acteurs, Usages, Institut de Recherche pour le Développement, University of North Carolina at Chapel Hill, Pennsylvania State University, Brown University, University of Illinois Urbana-Champaign, The University of Tokyo, Scripps Institution of Oceanography, University of California San Diego, Tsinghua University, Jet Propulsion Laboratory, Virginia Tech, Laboratoire d’Études en Géophysique et Océanographie Spatiales, United States Geological Survey, University of Stuttgart, University of Chicago
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,190
OpenAlex ID: W7204095203